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the evaluation of species-recovery options. An alternative approach would be to develop a landscape-level model that would be used to evaluate habitat management options.

Georges Bank Fishery

As described in the case study, models are used extensively to assess the status of exploited fish stocks to quantify the relationship between fishing intensity and future abundance. Risk characterizations clearly delineate the effects of alternative harvesting strategies. However, the management decision-making process was described by the case study author as being disconnected from the scientific risk assessment exercise. The consensus of the group was that an adaptive management process, in which management itself is viewed as an experimental tool, is needed. The implementation of such an approach would require a closer connection between stock-assessment scientists and fishery managers.

General Discussion: Models and Risk Assessment

There was general agreement that modeling should have a prominent role in risk assessment. The participants agreed that models provide the only means to perform ecological risk assessments on large physical and organizational scales. Modeling should prove especially valuable for the more complex risk assessments required in the future (e.g., for release of genetically engineered organisms). It was clear from the case studies that models are being used in some settings. However, no consistent integration of modeling into risk assessment was evident. In particular, models were not routinely used in risk characterization or in evaluation of management alternatives. The Georges Bank assessment made the most extensive use of models, but even here the results of modeling did not appear to influence decision-making.

The group advanced a number of explanations for the lack of influence of models on risk management decisions:



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APPENDIX F 326 original typesetting files. Page breaks are true to the original; line lengths, word breaks, heading styles, and other typesetting-specific formatting, however, cannot be About this PDF file: This new digital representation of the original work has been recomposed from XML files created from the original paper book, not from the retained, and some typographic errors may have been accidentally inserted. Please use the print version of this publication as the authoritative version for attribution. the evaluation of species-recovery options. An alternative approach would be to develop a landscape-level model that would be used to evaluate habitat management options. Georges Bank Fishery As described in the case study, models are used extensively to assess the status of exploited fish stocks to quantify the relationship between fishing intensity and future abundance. Risk characterizations clearly delineate the effects of alternative harvesting strategies. However, the management decision- making process was described by the case study author as being disconnected from the scientific risk assessment exercise. The consensus of the group was that an adaptive management process, in which management itself is viewed as an experimental tool, is needed. The implementation of such an approach would require a closer connection between stock-assessment scientists and fishery managers. General Discussion: Models and Risk Assessment There was general agreement that modeling should have a prominent role in risk assessment. The participants agreed that models provide the only means to perform ecological risk assessments on large physical and organizational scales. Modeling should prove especially valuable for the more complex risk assessments required in the future (e.g., for release of genetically engineered organisms). It was clear from the case studies that models are being used in some settings. However, no consistent integration of modeling into risk assessment was evident. In particular, models were not routinely used in risk characterization or in evaluation of management alternatives. The Georges Bank assessment made the most extensive use of models, but even here the results of modeling did not appear to influence decision-making. The group advanced a number of explanations for the lack of influence of models on risk management decisions: